About:
RLPy is a framework for performing reinforcement learning (RL) experiments in Python. RLPy provides a large library of agent and domain components, and a suite of tools to aid in experiments (parallelization, hyperparameter optimization, code profiling, and plotting).

Changes:

Fixed bug where results using same random seed were different with visualization turned on/off

Created RLPy package on pypi (Available at https://pypi.python.org/pypi/rlpy)

About:
Caffe aims to provide computer vision scientists with a clean, modifiable implementation of state-of-the-art deep learning algorithms. We believe that Caffe is the fastest available GPU CNN implementation. Caffe also provides seamless switching between CPU and GPU, which allows one to train models with fast GPUs and then deploy them on non-GPU clusters. Even in CPU mode, computing predictions on an image takes only 20 ms (in batch mode).

About:
ARTOS can be used to quickly learn models for visual object detection without having to collect a set of samples manually. To make this possible, it uses ImageNet, a large image database with more than 20,000 categories.

About:
PyStruct is a framework for learning structured prediction in Python. It has a modular interface, similar to the well-known SVMstruct. Apart from learning algorithms it also contains model formulations for popular CRFs and interfaces to many inference algorithm implementation.

About:
peewit provides services for programming, running and result examination of machine learning experiments. It does not include any ML algorithms, has no GUI, and presumes certain uniformity of the experimental layout. But it does not make assumptions on the type of task under study. The current version-number is 0.10.

About:
Bob is a free signal-processing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, in Switzerland.

Changes:

Bob 1.2.0 comes about 1 year after we released Bob 1.0.0. This new release comes with a big set of new features and lots of changes under the hood to make your experiments run even smoother. Some statistics:

About:
ClowdFlows is a web based platform for service oriented data mining publicly available at http://clowdflows.org . A web based interface allows users to construct data mining workflows that are hosted on the web and can be (if allowed by the author) accessed by anyone by following a URL of the workflow.

About:
This package includes implementations of the CCM, DMV and DMV+CCM parsers from Klein and Manning (2004), and code for testing them with the WSJ, Negra and Cast3LB corpuses (English, German and Spanish respectively). A detailed description of the parsers can be found in Klein (2005).

About:
A collection of python code to perform research in optimization. The
aim is to provide reusable components that can be quickly applied to
machine learning problems.
Used in:
- Ellipsoidal multiple instance learning
- difference of convex functions algorithms for sparse classfication
- Contextual bandits upper confidence bound algorithm (using GP)
- learning output kernels, that is kernels between the labels of a classifier.

About:
HDDM is a python toolbox for hierarchical Bayesian parameter
estimation of the Drift Diffusion Model (via PyMC).
Drift Diffusion Models are used widely in psychology and cognitive
neuroscience to study decision making.

Changes:

New and improved HDDM model with the following changes:

Priors: by default model will use informative priors
(see http://ski.clps.brown.edu/hddm_docs/methods.html#hierarchical-drift-diffusion-models-used-in-hddm)
If you want uninformative priors, set informative=False.

Sampling: This model uses slice sampling which leads to faster
convergence while being slower to generate an individual
sample. In our experiments, burnin of 20 is often good enough.

Inter-trial variablity parameters are only estimated at the
group level, not for individual subjects.

About:
Orange is a component-based machine learning and data mining software. It includes a friendly yet powerful and flexible graphical user interface for visual programming. For more advanced use(r)s, [...]

Changes:

The core of the system (except the GUI) no longer includes any GPL code and can be licensed under the terms of BSD upon request. The graphical part remains under GPL.

Changed the BibTeX reference to the paper recently published in JMLR MLOSS.